1. Field of the Invention
The present invention relates to an environment recognition device and an environment recognition method for recognizing a target object based on a luminance of the target object in a detection area.
2. Description of Related Art
Conventionally, a technique has been known that detects a target object such as an obstacle including a vehicle and a traffic light located in front of a subject vehicle for performing control to avoid collision with the detected target object and to maintain a safe distance between the subject vehicle and the preceding vehicle (for example, Japanese Patent No. 3349060 (Japanese Patent Application Laid-Open (JP-A) No. 10-283461)).
Further, in such techniques, there is a technique that performs more advanced control. Specifically, it not only specifies a target object uniformly as a solid object, but further determines whether the detected target object is a preceding vehicle that is running at the same speed as the subject vehicle or a fixed object that does not move. In this case, when the target object is detected by capturing an image of a detection area, it is necessary to extract (cut out) the target object from the captured image before specifying what the target object is.
For example, there is known a technique that recognizes, when the captured image is a color image, a light source such as a traffic light as a target object by grouping a set of pixels with a same luminance (color) (for example, JP-A No. 2010-224925). However, such a target object may change in color due to an influence of environmental light such as sunlight and illumination light. A solution for removing the influence of the environmental light may be performing a white balance correction on the captured image. For example, there is known a technique that extracts a region corresponding to a road surface from a captured image and performs the white balance correction thereon (for example, JP-A No. 2006-338555).
When a subject vehicle is driving on a road, the road occupies a detection area in many cases. Thus, on the premise that the road surface is gray, it is preferable to extract a region corresponding to the road surface and to perform a white balance correction such that the road surface becomes gray. However, a typical road surface has a portion such as a school zone whose color is different from gray (for example, green). If a white balance correction that simply makes a conversion to gray is performed on a road surface colored with a color different from gray, the white balance in the detection area is lost.
Since there are fewer roads colored with a color different from gray than roads colored gray, a solution for avoiding such a circumstance may be excluding such roads with a low-pass filter. However, since roads with a color different from gray are not always short, it is difficult to uniquely define a parameter for the low-pass filter. Further, in the case of an entrance of a tunnel and the like, where environment light drastically changes, delay due to the filter may affect responsiveness of control.